0213 Latent Typologies of College Students’ Sleep-related Habits and Behaviors

Abstract Introduction With 43% of college students obtaining less than the recommended 7-9 hours of sleep per night and with over 75% reporting feeling tired/sleepy most days of the week (American College Health Association, 2023), this population is at significant risk for mental health, physical, and academic problems (Gaultney, 2010; Peltz & Rogge, 2016). Research has tended to focus on links between deficient sleep and negative outcomes via variable-center approaches (e.g., linear modeling), which may fail to capture individuals who exhibit multivariate sleep patterns (Yue et al., 2022). The present study used a latent profile analysis to identify subpopulations based on an extensive group of sleep-related habits and behaviors endorsed by a large sample of college students. Methods The current sample’s mean age (N=638, 82.4% female) was 21.3 years (SD=2.4; range 18-34), and 64.3% of participants were white, with 19.6% Asian/Pacific Islander, 6.9% Black, 6.7% Hispanic/Latinx, and 2.5% multi-racial or “other.” Approximately 60.5% of the sample lived on campus, and 56.8% maintained part- or full-time employment while attending school. The sleep-related habits and behaviors included in the latent profile analysis included the following scales: sleep disturbance, daytime impairment, environmental noise, sleep environment, sleep competency, sleep hygiene, work hours, problematic smartphone use, chronotype, and melatonin usage. Results Five sleep classes were identified including two more adaptive groups (great sleepers-23% & typical sleepers-35%), and three groups reporting greater sleep challenges (poor but conscientious sleepers-19%, poor sleepers-20%, & self-sabotaging sleepers-3%). The two adaptive groups reported fewer depressive/anxiety symptoms and higher GPAs, whereas the groups reporting disrupted sleep reported greater depressive/anxiety symptoms, life stress, and lower GPAs. The poor but conscientious sleepers were distinguished by better sleep environments and sleep hygiene (with slightly lower impairment), whereas the sabotaged sleepers were distinguished by poorer sleep hygiene, sleep environments, and greater problematic phone and alcohol use (with slightly greater impairment). Regressions predicting individual, interpersonal, and adaptive functioning highlighted that the typologies contributed unique predictive validity toward understanding college student functioning. Conclusion Our results highlight the diversity of sleep typologies present in college students. Students falling into poor/problematic sleep groups remain at risk for negative psychosocial and other health-related outcomes. Support (if any)